LEVERAGING CLOUD-BASED ANALYTICS FOR PERFORMANCE OPTIMIZATION IN INTELLIGENT BUILDING SYSTEMS
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Abstract
The rise of intelligent building systems (IBS) is transforming energy use, environmental quality, and occupant interaction in modern infrastructure. Cloud-based analytics plays a central role by integrating with IoT and edge systems to offer scalable data collection, real-time analysis, and AI insights. This paper explores how cloud analytics enhances energy efficiency, thermal comfort, and reliability in IBS. It presents an architectural framework covering data ingestion, processing, and visualization, supported by case studies from smart airports and commercial complexes. The study identifies technological drivers, algorithmic strategies, and deployment challenges, concluding with future directions in edge-cloud orchestration, privacy-aware learning, and smart city integration.
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References
1. International Energy Agency (IEA), “Digitalization and energy 2022,” [Online]. Available: https://www.iea.org/reports/digitalisation-and-energy
2. KubeEdge, “KubeEdge: Extending native containerized application orchestration capabilities to hosts at edge,” [Online]. Available: https://kubeedge.io
3. M. Zandi, B. Farokhi, and P. Scott, “Reinforcement learning for HVAC control in smart buildings: A review,” IEEE Transactions on Smart Grid, vol. 13, no. 4, pp. 3427–3440, Jul. 2022.
4. Autodesk Forge, “Forge Platform for Digital Twins and BIM,” [Online]. Available: https://forge.autodesk.com
5. D. H. Lee, “Towards net-zero energy buildings: Integration of building energy simulation with AI-based forecasting models,” Renewable and Sustainable Energy Reviews, vol. 138, no. 110641, 2021.
6. S. Shaikh and M. A. Rahman, “IoT and cloud computing based intelligent energy management system for smart buildings,” Journal of Building Engineering, vol. 45, no. 103455, 2021.